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This project involved developing embedded firmware for a NASA-affiliated research initiative focused on environmental data collection. The system used a network of ESP32 microcontrollers equipped with environmental sensors to collect, process, and transmit real-time data to cloud infrastructure for analysis.
The firmware was written in C++ using the ESP-IDF framework, with a strong emphasis on power efficiency, reliability, and accurate sensor calibration — requirements that are especially demanding in field-deployed IoT systems.
Hardware Setup
Sensor Array
Data Dashboard
Field Deployment
Field-deployed IoT devices face unique engineering constraints: limited power budgets, unreliable wireless connectivity, harsh environmental conditions, and zero tolerance for data loss. Every design decision had to balance performance against power consumption.
Additionally, the multi-node sensor network required a robust communication protocol that could handle intermittent connectivity, packet loss, and out-of-order delivery — all while maintaining data integrity for scientific purposes.
Designed a mesh-adjacent sensor node architecture with a central gateway ESP32 coordinating data aggregation from edge nodes via ESP-NOW protocol for low-latency, connectionless communication.
Wrote production C++ firmware with deep sleep power management, watchdog timer recovery, OTA (over-the-air) update capability, and deterministic sensor sampling intervals.
Built the cloud integration layer using MQTT over TLS, with a Python-based ingestion service on AWS IoT Core feeding data into S3 for research analysis.
Performed extensive sensor calibration, stress testing, and field validation to ensure measurement accuracy and system stability over extended deployment periods.
The deployed system achieved exceptional reliability in field conditions, with consistent data collection across all sensor nodes. The power management optimizations exceeded battery life projections, and the data pipeline successfully processed thousands of sensor readings per day with zero data loss.
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